arXiv 2604.005402026-04-01eess.SYcs.NAcs.SYmath.NA

网络韧性评估与控制的序贯蒙特卡洛方法

Sequential Monte Carlo for Network Resilience Assessment and Control

University of Oulu（奥卢大学）

Onel Luis Alcaraz López

备注：: 7 pages, 3 figures, 1 table

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AI总结：

本文提出一种序贯蒙特卡洛框架，用于评估和控制网络系统中的韧性，通过多级分裂和自适应种群控制机制，有效估计稀有非恢复概率并实现政策驱动的恢复。

摘要：

韧性正成为下一代无线通信系统的关键要求，需能评估和控制由顺序退化和延迟恢复引发的罕见、路径依赖性故障事件。本文开发了一种序贯蒙特卡洛（SMC）框架，用于网络系统的韧性评估与控制。韧性故障被建模为分阶段、路径依赖事件，并通过基于反应坐标的分解方法捕捉向非恢复发展的进程。在此基础上，提出了一种具有固定、语义可解释层级的多级分裂方法和预算自适应的种群控制机制，动态分配计算资源以满足固定总模拟成本。该框架进一步扩展以纳入缓解策略，通过利用SMC检查点进行策略评估、比较和状态依赖性选择。通过一个延迟关键的无线网络案例演示了该方法。数值结果表明，所提出的SMC方法在估计稀有非恢复概率方面显著优于标准蒙特卡洛方法，并在不同系统条件下实现有效的政策驱动恢复。结果突显了SMC作为未来通信系统中面向韧性的分析和控制实用工具的潜力。

英文摘要：

Resilience is emerging as a key requirement for next-generation wireless communication systems, requiring the ability to assess and control rare, path-dependent failure events arising from sequential degradation and delayed recovery. In this work, we develop a sequential Monte Carlo (SMC) framework for resilience assessment and control in networked systems. Resilience failures are formulated as staged, path-dependent events and represented through a reaction-coordinate-based decomposition that captures the progression toward non-recovery. Building on this structure, we propose a multilevel splitting approach with fixed, semantically interpretable levels and a budget-adaptive population control mechanism that dynamically allocates computational effort under a fixed total simulation cost. The framework is further extended to incorporate mitigation policies by leveraging SMC checkpoints for policy evaluation, comparison, and state-contingent selection via simulation-based lookahead. A delay-critical wireless network use case is considered to demonstrate the approach. Numerical results show that the proposed SMC method significantly outperforms standard Monte Carlo in estimating rare non-recovery probabilities and enables effective policy-driven recovery under varying system conditions. The results highlight the potential of SMC as a practical tool for resilience-oriented analysis and control in future communication systems.

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